Using Artificial Intelligence Across Firm Roles

Artificial intelligence (AI) deals with giving machines and software the appearance of human intelligence. By that definition, the legal profession poses a challenge for AI, as, often, the answers to legal questions are not definitive, but rather more nuanced interpretations and judgments of a law.

There are exceptions to this, of course, in practice areas with very defined rule sets, such as compliance, regulatory and immigration. Additionally, the legal profession is very document-heavy, and many of the tasks associated with reading and producing documents can now be automated.

To date, most of the focus introducing AI into the legal profession has been centered on the practice of law. Electronic discovery (also known as e-Discovery) laid the groundwork for utilizing machine learning and natural language processing with technology-assisted review, followed by products like Lex Machina that ventured into predictive analytics.

In recent years, companies like Kira, RAVN and KM Standards have created a niche in contract analytics with machine learning and natural language processing. Meanwhile, ROSS Intelligence, Ravel Law and others have brought various AI methodologies to legal research, and companies such as Neota Logic have introduced platform-based expert systems to the legal profession.

The introduction of contract analytics and knowledge automation has changed, for example, the speed at which document-heavy transactions, such as commercial leases in real estate, are reviewed, with risk assessments and lease valuations performed in minutes by automating the judgment and expertise of counsel. While some law firms struggle with employing such technology, the buyers of legal services are taking notice. In the constant struggle to reduce legal spend, buyers of legal services see the promise of AI and knowledge automation coming to fruition.

These resources offer the opportunity to reduce a centuries-old problem of constant cost, where every unit of output for law firms typically costs the same as the last, making it exceedingly difficult to scale many practices. In recent years, knowledge management, legal project management and process improvement have made tremendous strides in increasing law firm efficiency, but many continue to consolidate staff and timekeeper roles in an effort to maintain profitability. This is where multiple AI technologies can impact the administrative functions within firms.

Like the practice of law, the pricing of legal services has often become bespoke, thus creating some challenges for scalability. Many firms have a variety of decision trees that help attorneys and staff decide on specific fee agreements, as well as Excel files filled with staffing and pricing formulas. This can easily create a bottleneck, especially for larger firms with multiple offices. Knowledge automation applications can be created by firms that will ask questions that range from basic intake, such as client name, type of matter and more to what the goals of the client are regarding the fee objective.

For example, is the client looking for consistent and predictable cost across matters with a well-defined scope, or is the demand more around lower-fixed costs with some element of shared risk? Numerous pointed questions can be asked, and the application can have pre-negotiated discounts, outside counsel guideline restrictions and other considerations built in to gather facts and apply the pricing professional’s reasoning to reach conclusions and execute actions.

Marketing and business development functions of law firms are finding multiple uses for AI as well. Consider the example noted earlier with contract analytics involving real estate leases. This example could easily apply to RFPs, utilizing the weighting algorithm to identify the individual components of the RFP that pose the greatest risk, and providing an overall “go/no-go” assessment to that RFP. Given the amount of time spent on RFP evaluation prior to the resource time utilized to respond to the RFP, combined with the relatively low success rate, this should be a welcome and immediate leveraging of technology.

Ethics rules governing attorney advertising can be a persistent challenge for firms with numerous offices; an application that assesses the firm’s compliance to the various and applicable state bar rules with all marketing materials can be powerful. Client-facing applications, whether monetized directly or provided as a “value-add,” will also become an integral part of a firm’s client development strategy.

Overall, the important point to keep in mind is that AI isn’t necessarily “artificial” intelligence; rather, it is the expertise and intelligence of the professionals combined with the law and precedent, applied at scale.

Patrick Fuller is the Vice President of Neota Logic, Inc. He is frequent speaker and author on the business of law and legal technology. He has served as the Director of Legal Analytics for TyMetrix Legal Analytics, a Senior Consultant for LawVision Group, and the Managing Director of Monitor Suite at Thomson Reuters. He is a 2017 Fellow-elect to The College of Law Practice Management.